Evidence map›Paper›PMID 29130072›Full record

ArticleKidney international reports2017

Prediction of Chronic Kidney Disease Stage 3 by CKD273, a Urinary Proteomic Biomarker.

Claudia Pontillo, Zhen-Yu Zhang, Joost P Schanstra, Lotte Jacobs, Petra Zürbig, Lutgarde Thijs, Adela Ramírez-Torres, Hiddo J L Heerspink, Morten Lindhardt, Ronald Klein and 15 more

Abstract read
In one paragraph

Article in Kidney international reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

45 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Trial
  4. Article
  5. Review
  6. Review
  7. Article
  8. Article
  9. Urinary peptide analysis to predict the response to blood pressure medication.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2024
    Article
  10. Review
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Review
  18. Novel biomarkers for diabetic kidney disease.Kidney research and clinical practice · 2022
    Article
  19. Urine proteomics for prediction of disease progression in patients with IgA nephropathy.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2021
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

25 authors.

Claudia PontilloMosaiques Diagnostics GmbH, Hannover, Germany.
Zhen-Yu ZhangStudies Coordinating Centre, Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Diseases, University of Leuven, Leuven, Belgium.
Joost P SchanstraInstitute of Cardiovascular and Metabolic Disease, Institut National de la Santé et de la Recherche Médicale (INSERM), Toulouse, France.
Lotte JacobsStudies Coordinating Centre, Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Diseases, University of Leuven, Leuven, Belgium.
Petra ZürbigMosaiques Diagnostics GmbH, Hannover, Germany.
Lutgarde ThijsStudies Coordinating Centre, Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Diseases, University of Leuven, Leuven, Belgium.
Adela Ramírez-TorresSanford Burnham Prebys Medical Discovery Institute, La Jolla, California, USA.
Hiddo J L HeerspinkDepartment of Clinical Pharmacy and Pharmacology, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands.
Morten LindhardtSteno Diabetes Centre, Gentofte, Denmark.
Ronald KleinDepartment of Ophthalmology and Visual Sciences, University of Wisconsin School of Medicine and Public Health, Madison Wisconsin, USA.
Trevor OrchardDepartment of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Massimo PortaDepartment of Medical Sciences, University of Turin, Torino, Italy.
Rudolf W BilousInstitute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, UK.
Nishi CharturvediInstitute of Cardiovascular Sciences, University College London, London, UK.
Peter RossingSteno Diabetes Centre, Gentofte, Denmark.
Antonia VlahouBiotechnology Division, Biomedical Research Foundation, Academy of Athens, Athens, Greece.
Eva SchepersNephrology Section, Department of Internal Medicine, Ghent University Hospital, Ghent, Belgium.
Griet GlorieuxNephrology Section, Department of Internal Medicine, Ghent University Hospital, Ghent, Belgium.
William MullenInstitute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK.
Christian DellesInstitute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK.
Peter VerhammeCentre for Molecular and Vascular Biology, KU Leuven Department of Cardiovascular Sciences, University of Leuven, Leuven, Belgium.
Raymond VanholderNephrology Section, Department of Internal Medicine, Ghent University Hospital, Ghent, Belgium.
Jan A StaessenStudies Coordinating Centre, Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Diseases, University of Leuven, Leuven, Belgium.
Harald MischakMosaiques Diagnostics GmbH, Hannover, Germany.
Joachim JankowskiUniversity Hospital, Rheinisch-Westfälische Technische Hochschule Aachen, Aachen, Germany.

Funding

European Research Council 294713
6 · The paper itself

Abstract

introductionCKD273 is a urinary biomarker, which in advanced chronic kidney disease predicts further deterioration. We investigated whether CKD273 can also predict a decline of estimated glomerular filtration rate (eGFR) to <60 ml/min per 1.73 m

methodsIn analyses of 2087 individuals from 6 cohorts (46.4% women; 73.5% with diabetes; mean age, 46.1 years; eGFR ≥ 60 ml/min per 1.73 m

resultsOver 5 (median) follow-up visits, eGFR decreased more with higher baseline CKD273 than UAE (1.64 vs. 0.82 ml/min per 1.73 m DISCUSSION: In conclusion, while accounting for baseline eGFR, albuminuria, and covariables, CKD273 adds to the prediction of stage 3 chronic kidney disease, at which point intervention remains an achievable therapeutic target.

Indexed as

biomarkerchronic kidney diseaseclinical scienceglomerular filtration ratepeptidomicsproteomics

Identifiers

PMID29130072
PMCPMC5669285

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.